Advertisement modification method and apparatus

ABSTRACT

Television transmissions are received at multiple locations across a large area. Advertisements may be identified, harvested and tagged from within in the television transmissions. The advertisements may be assigned identifiers; media plans may be determined. Advertisement representations (e.g. fingerprints) may be used to identify advertisements in television content received by the smart TVs. The smart TVs may report the fingerprints along with other identifiers or samples thereof. Television content and advertisements therein as rendered by the smart TVs may be categorized as live, timeshifted, on-demand, over-the-top, and the like. The advertisements may be categorized as occurring in national or local/regional ad slots. The data from the smart TVs may be used to determine ad impressions, gross rating points, and target rating points. View rates for advertisements may also be determined and variations of advertisement may also be prepared.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 15/218,351, filed Jul. 25, 2016; U.S. patent application Ser.No. 15/218,351 is a continuation of U.S. patent application Ser. No.14/489,359, filed Sep. 17, 2014. U.S. patent application Ser. Nos.14/489,359 and 15/218,351 are incorporated herein, in their entirety,for all purposes; the benefit of the filing date of U.S. patentapplication Ser. Nos. 14/489,359 and 15/218,351 are claimed for allsubject matter disclosed therein.

FIELD

This disclosure relates to a method and system for measuringimpressions, audience size, and behavioral characteristics of televisioncommercials and viewers of television commercials.

BACKGROUND

The following description includes information that may be useful inunderstanding the present invention. It is not an admission that any ofthe information provided herein is prior art or relevant to thepresently claimed invention, or that any publication specifically orimplicitly referenced is prior art.

Television audience measurement technologies use human-completed paperlogs, somewhat automated “People Meters”, and, more recently, moreautomated “Portable People Meters” and analysis of “Set-Top Box” data.Paper logs are notebooks in which research subjects record whattelevision broadcast channels and shows they watch and at what time. Thepaper logs are criticized for being imprecise or inaccurate, forunder-reporting daytime and late-night viewing, for failing to recordchannel “surfing” (rapidly changing channels), and for only measuringaudience behavior during relatively few periods during the year. PeopleMeters have buttons, generally one for each research subject in aresidence. The research subject presses a button to indicate that theyare watching the television and the People Meter records what frequencythe television is tuned to. By cross-referencing the time of day with abroadcast schedule for the channel utilizing the frequency, it ispossible to determine the program which the research subject wasprobably watching (assuming there were no deviations from the schedule).

People Meters also allow non-research subjects to input their age andother demographic information (via buttons), so that non-researchsubjects may also provide information. Paper logs and People Meters arecriticized for requiring active engagement by the research subject, forthe selection and distribution of research subjects across thepopulation, for only being used inside of residences, for not measuringaudience behavior with respect to non-traditional media renderingdevices (smart phones, tables, laptop and desktop computers, and thelike), and for the inexact connection between program schedule and whatprograms and advertisements were actually viewed. Portable People Meters(“PPM”) are devices worn on or carried by a research subject. The PPMdetects inaudible information encoded in the airchain and transmits thedecoded information to the research organization. The decodedinformation identifies the media which the research subject was exposedto.

Set-Top Box data from cable converter boxes and the like has been usedmore recently to measure audience sizes and characteristics. Set-TopBoxes have a large installed base, the data is easily accessible andthere is readily available demographic data at the household level.However, one of the major weaknesses in Set-Top Box data is theinability to verify whether the television screen is actually on andwhether the content is being viewed since many people turn off theirtelevisions without turning off the Set-Top Box. This leaves measurementcompanies guessing and creating algorithms to guess what was actuallyviewed. The second issue with Set-top Box data is not knowingdefinitively what advertisements ran during a program and requiresmatching of external “as-run ad logs” to determine what ads may havebeen viewed. This is further complicated by certain advertisement typesthat are locally inserted, operator inserted, dynamically inserted, orinserted into an “over-the-top” program transmission (programtransmission on Netflix, Hulu, and the like is referred to herein as an“over-the-top” or “OTT” transmission). The tracking of advertisements inon-demand programming, OTT programming, and other types ofadvertisements is virtually impossible via Set-Top Box data.

Previous audience measuring systems are very dependent on the accuracyof a media plan, which is used to determine what the research subjectwas exposed to; however, anticipated media plans are notorious for beinginaccurate relative to what was actually broadcast. Furthermore,existing audience measuring systems are slow, do not record many forumsand devices in which and by which media is rendered, and are orientedaround shows and show audiences, rather than advertisements andadvertisement audiences.

Many “second screen” services exist to provide content on a secondscreen, such as a smartphone, while a user watches or is present beforea first screen. To provide relevant second screen content, such servicesrequire knowing what is being rendered on the first screen. Automaticcontent recognition (“ACR”) is being deployed to automatically recognizecontent, such as based on recognition of fingerprints or watermarks.However, as the amount of content increases rapidly and as advertiserscreate more narrowly tailored advertisements and rapidly place them inwide-ranging distribution channels, including in broadcast media (suchthat advertisement content increases even faster than non-advertisementcontent), it is not realistic to insert watermarks into all content andfingerprint recognition requires a vast and highly organizedinfrastructure to characterize the ever-expanding pool of content. As aresult, ACR is typically focused on recognizing “shows” in the content,not on recognizing advertisements.

Advertisers attempt to measure the “View Rate” for advertisements (“ViewRate” is defined further, herein). However, for broadcastadvertisements, the equipment used to measure View Rate is not typicallylocated in the television (or other display device) which renders theadvertisement, but is located elsewhere in the path to the television,such as in a Set-Top Box or on a server. Attempting to measure View Ratein the path to the television is problematic, because of disconnectswhich can occur between the television and the path to the televisionand because not all users will be connected to a sampled path. As aresult, View Rate measurement, particularly with respect to broadcastmedia, typically uses small, closely studied, audiences with controlledequipment and/or with limited content access and statisticalextrapolation of the resulting information to larger audiences.

Needed is a system and method to accurately measure and verify theexposure and make-up of audiences of television advertisements, whetherthe advertisements are in linear television, on-demand, OTT, or playedvia the Internet (e.g. via Chromecast or the like). Also needed is asystem and method to accurately measure, based on data from diversereal-world televisions, View Rates of advertisements in broadcast mediaand other media across large populations.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a network and device diagram illustrating exemplary computingdevices configured according to embodiments disclosed in this paper.

FIG. 2 is a functional block diagram of an exemplary iSpot Servercomputing device and some data structures and/or components thereof.

FIG. 3 is a functional block diagram of an exemplary iSpot ServerDatastore.

FIG. 4 is a functional block diagram of an exemplary Smart TV computingdevice and some data structures and/or components thereof.

FIG. 5 is a functional block diagram of an exemplary Smart TV Datastore.

FIG. 6 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of an Ad Harvester routine.

FIG. 7 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a Media Plan Determiner routine.

FIG. 8 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a Viewing Data Collector routine.

FIG. 9 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a Smart TV Data Collector routine.

FIG. 10A is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a first portion of an Ad Insertion TypeDeterminer routine

FIG. 10B is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a second portion of an Ad Insertion TypeDeterminer routine.

FIG. 11A is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a first portion of a New Ad Identifier routine.

FIG. 11B is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a second portion of a New Ad Identifierroutine.

FIG. 12 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a View Rate module.

FIG. 13A is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a first portion of an Overlap and Behaviormodule.

FIG. 13B is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a second portion of an Overlap and Behaviormodule.

FIG. 14 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a Benchmark Determining module.

FIG. 15 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a Reference Ad and Variation module.

DETAILED DESCRIPTION

The following Detailed Description provides specific details for anunderstanding of various examples of the technology. One skilled in theart will understand that the technology may be practiced without many ofthese details. In some instances, structures and functions have not beenshown or described in detail or at all to avoid unnecessarily obscuringthe description of the examples of the technology. It is intended thatthe terminology used in the description presented below be interpretedin its broadest reasonable manner, even though it is being used inconjunction with a detailed description of certain examples of thetechnology. Although certain terms may be emphasized below, anyterminology intended to be interpreted in any restricted manner will beovertly and specifically defined as such in this Detailed Descriptionsection.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense; that is to say, in the sense of“including, but not limited to.” As used herein, the term “connected,”“coupled,” or any variant thereof means any connection or coupling,either direct or indirect between two or more elements; the coupling ofconnection between the elements can be physical, logical, or acombination thereof. Additionally, the words, “herein,” “above,”“below,” and words of similar import, when used in this application,shall refer to this application as a whole and not to particularportions of this application. When the context permits, words using thesingular may also include the plural while words using the plural mayalso include the singular. The word “or,” in reference to a list of twoor more items, covers all of the following interpretations of the word:any of the items in the list, all of the items in the list, and anycombination of one or more of the items in the list.

Multiple instances of certain components are labeled with an elementnumber and letter; all such component instances are equivalent withinnormal ranges. Multiple instances of otherwise identical components cancontrol, be controlled, or communicate separately through assignment ofunique or distinguishing identifiers. Such components may be referred toherein only by element number, without a letter in conjunctiontherewith, in which case the reference is to any of such components.

As used herein, “TV” is an abbreviation for “television”.

As used herein, “on-demand programming” means audio and/or video contentwhich a user selects; the on-demand programming is typically selectedand viewed in real-time, though the programming may also be downloadedor otherwise recorded (by a computing device proximate to the end useror at a server remote from the end user) for later viewing or rendering.

As used herein, “linear television” means television programming whichis broadcast on a pre-established schedule to a large audience.

As used herein, “Smart TV” is a television or set-top box with anintegrated computer and Internet services. Smart TVs can access andrender broadcast television programming as well as online interactivemedia, Internet TV, OTT content, and network-accessible content,typically through a downloaded or pre-installed software application or“app”. Smart TVs are computers comprising a memory, an operating system,and applications for receiving and rendering broadcast televisionprogramming and content obtained through apps.

As used herein, “Operator” is an organization which provides content viaTV Distribution Media. Operators may aggregate content from multipleTelevision Networks, each of which may be assigned a “channel” orequivalent in the Broadcast Media.

As used herein, “TV Distribution Media” is a one-to-many communicationmedium which generally utilizes electro-magnetic radiation to transmitinformation; examples of TV Distribution Media include radio andtelevision terrestrial broadcast media, satellite broadcast media, andcable systems.

As used herein, “TV Network” is a distributor of linear televisioncontent, generally allocated one or more “channels” in TV DistributionMedia. TV Networks commonly, though not exclusively, distribute lineartelevision content through Operators, such as through a cable company.TV Networks may distribute linear television content directly throughcertain types of TV Distribution Media, such as through terrestrialbroadcast media.

As used herein, “Pod” means a cluster of consecutive commercials or spotannouncements within a television show.

As used herein, “Ad Slot” means a portion of a Pod in which anadvertisement may be inserted. A Pod generally comprises multiple AdSlots.

As used herein, “View Rate” measures the percentage of a broadcastadvertisement which is viewed or at least rendered on a display device,such as a television. View Rate as used herein should not be confusedwith view-through rate in the context of online advertisements;view-through rate measures post-impression response or “viewthrough”from display media impressions viewed during and following an onlineadvertising campaign and is generally understood as100*viewthrough/impressions.

As used herein, “daypart” is a division of a week into days of the week,weekdays, weekends, and a division of days into, for example, primetime,early fringe, late fringe PM, weekend afternoon, late fringe AM, daytime, weekend day, early morning, overnight, and the like.

As used herein, the term “module”, “logic”, and “routine” may refer to,be part of, or include an Application Specific Integrated Circuit(ASIC), a System on a Chip (SoC), an electronic circuit, a processor(shared, dedicated, or group) and/or memory (shared, dedicated, orgroup) or in another computer hardware component or device that executeone or more software or firmware programs or a combination, acombinational logic circuit, and/or other suitable components thatprovide the described functionality. Modules may be distinct andindependent components integrated by sharing or passing data, or themodules may be subcomponents of a single module, or be split amongseveral modules. The components may be processes running on, orimplemented on, a single compute node or distributed among a pluralityof compute nodes running in parallel, concurrently, sequentially or acombination, as described more fully in conjunction with the flowdiagrams in the figures.

FIG. 1 is a network and device diagram illustrating exemplary computingdevices configured according to embodiments disclosed in this paper.Illustrated is iSpot Server 200 computer, which iSpot Server 200connects to Smart TV 400 and Media Rendering Device 120 via network 199.

Smart TV 400 and Media Rendering Device 120 are illustrated withinLocation 175. Location 175 may be, for example, a house, an apartmentbuilding, or the like. Smart TV 400 and Media Rendering Device 120 donot have to be collocated (as illustrated in FIG. 1, within Location175), but may be located in different locations. iSpot Server 200 maycomprise or be connected to iSpot Datastore 300 (discussed furtherbelow). Illustrated within Media Rendering Device 120 are examples ofMedia Rendering Device 120, such as Computer 124 (which may be a laptop,desktop, tower computer and similar) and Mobile Device 122 (which may bea smart phone, mobile phone, tablet computer, wearable computer, andsimilar). Media Rendering Device 120 illustrates computers and/orequipment which users may utilize to render television and other contentobtained from TV Distribution Media 180 and from Network 199. MediaRendering Device 120 also interacts with the iSpot Server 200 (asdescribed further herein).

Also illustrated in FIG. 1 is Smart TV 400 and Smart TV Datastore 500,discussed further below.

Also illustrated in FIG. 1 are Operator 160, TV Network 185, and TVDistribution Media 180. These terms are defined above.

Also illustrated in FIG. 1 is iSpot TV Monitor 110. iSpot TV Monitor 110connects to TV Distribution Media 180 across a wide geographic area,analyses linear television content distributed on TV Distribution Media180, and transmits information to iSpot Server 200. iSpot TV Monitor 110may perform some or all of the routines attributed to iSpot Server 200;for example, some or all of Ad Harvester 600 routine may be performed byiSpot TV Monitor 110.

Also illustrated in FIG. 1 is 3^(rd) Party Computer 150. 3^(rd) PartyComputer 150 represents multiple parties, corporations, and the like whomay be sources of information, such as program schedules for lineartelevision distributed on TV Distribution Media 180, census data, andthe like.

Network 199 illustrated in FIG. 1 comprises computers, networkconnections among the computers, and software routines to enablecommunication between the computers over the network connections.Examples of the Network 199 comprise an Ethernet network, the Internet,and/or a wireless network, such as a GSM, TDMA, CDMA, EDGE, HSPA, LTE,LTE-Advanced or other network provided by a wireless service provider.Connection to the Network 199 may be via a wireless or wirelineconnection. More than one network may be involved in a communicationsession between the illustrated devices. Connection to the Network 199may require that the computers execute software routines which enable,for example, the seven layers of the OSI model of computer networking orequivalent in a wireless phone network.

This paper may discuss a first computer or computer process asconnecting to a second computer or computer process (such as the SmartTV 400 connecting to the iSpot Server 200) or to a correspondingdatastore (such as to iSpot Datastore 300); it should be understood thatsuch connections may be to, through, or via the other of the twocomponents (for example, a statement that Smart TV 400 connects with orsends data to the iSpot Server 200 should be understood as saying thatthe computing device may connect with or send data to the iSpotDatastore 300). References herein to “database” should be understood asequivalent to “Datastore.” Although illustrated as components integratedin one physical unit, the computers and databases may be provided bycommon (or separate) physical hardware and common (or separate) logicprocessors and memory components. Though discussed as occurring withinone computing device, the software routines and data groups used by thesoftware routines may be stored and/or executed remotely relative to anyof the computers through, for example, application virtualization.

In overview (described in greater detail, below), iSpot Server 200executes Ad Harvester 600 routine (potentially in conjunction with orusing iSpot TV Monitor 110) to identify advertisements in lineartelevision and to save information regarding the advertisements.

iSpot Server 200 also executes Media Plan Determiner 700 routine todetermine a media plan for advertisements based on data from AdHarvester 600 routine, and, with data from iSpot TV Monitor 110, tocategorize Ad Slots and Advertisements in television shows as“national”, “regional”, “local” and/or “dynamically inserted”.

In overview, Smart TV 400 (defined above) is owned or possessed by atelevision viewer. Smart TV 400 executes Viewing Data Collector 800 tocollect information regarding Smart TV 400, itself, as well as regardinglinear television transmitted via TV Distribution Media 180. ViewingData Collector 800 may also be executed, in whole or in part, by iSpotServer 200 (such as, for example, blocks 830 to 865). The informationcollected by Smart TV 400 regarding the Smart TV 400, itself, comprisesidentifiers of the Smart TV 400 and of an IP Address or the likeassigned to Smart TV 400 and the Designated Market Area (“DMA”) in whichthe Smart TV 400 is located. The information collected by Smart TV 400regarding linear television transmitted via TV Distribution Media 180comprises a channel which Smart TV 400 received and rendered, a networkcall sign which may be associated with the channel, a show identifier ofa show rendered by Smart TV 400 on the channel, and an iSpot Ad ID of anadvertisement in the show rendered by Smart TV 400.

In overview, iSpot Server 200 also executes Smart TV Data Collector 900to collect data from Viewing Data Collector 800, to execute Ad InsertionType Determiner 1000, to determine the number of advertisementimpressions which occur in the advertisement insertion type categoriesdetermined by Ad Insertion Type Determiner 1000, and to determine theGRP and TRP for advertisements. Ad Insertion Type Determiner 1000categorizes content rendered by Smart TV 400 as being live or timeshifted, categorizes non-national advertisement insertions as beingregional or dynamic, and categorizes programming sources as beingon-demand, OTT, or Internet.

FIG. 2 is a functional block diagram of an exemplary iSpot Server 200computing device and some data structures and/or components thereof.iSpot Server 200 comprises at least one Processing Unit 210, iSpotServer Memory 250, Display 240 and Input 245, all interconnected alongwith Network Interface 230 via Bus 220. Processing Unit 210 may compriseone or more general-purpose Central Processing Units (“CPU”) 212 as wellas one or more special-purpose Graphics Processing Units (“GPU”) 214.

The components of Processing Unit 210 may be utilized by OperatingSystem 255 for different functions required by routines executed byiSpot Server 200. Network Interface 230 may be utilized to formconnections with Network 199 or to form device-to-device connectionswith other computers. iSpot Server Memory 250 generally comprises arandom access memory (“RAM”), a read only memory (“ROM”), and apermanent mass storage device, such as a disk drive or SDRAM(synchronous dynamic random-access memory). iSpot Server Memory 250stores program code for software routines, such as, for example, AdHarvester 600, Media Plan Determiner 700, Smart TV Data Collector 900,Ad Insertion Type Determiner 1000, as well as, for example, browser,email client and server routines, client applications, and databaseapplications (discussed further below). Additional data groups forroutines, such as for a webserver and web browser, may also be presenton and executed by the iSpot Server 200. Webserver and browser routinesmay provide an interface for interacting with the other computingdevices illustrated in FIG. 1 or with other computing devices notillustrated in FIG. 1, for example, through webserver and web browserroutines (which may serve and respond to data and information in theform of webpages and html documents or files). The browsers andwebservers are meant to illustrate user- and machine-interface routinesgenerally, and may be replaced by equivalent routines for serving andrendering information to and in an interface in a computing device(whether in a web browser or in, for example, a mobile deviceapplication, or an API call to a server, a library, or the like).

In addition, iSpot Server Memory 250 also stores Operating System 255.These software components may be loaded from a non-transient ComputerReadable Storage Medium 295 into iSpot Server Memory 250 of thecomputing device using a drive mechanism (not shown) associated with anon-transient Computer Readable Storage Medium 295, such as a floppydisc, tape, DVD/CD-ROM drive, memory card, or other like storage medium.In some embodiments, software components may also or instead be loadedvia a mechanism other than a drive mechanism and Computer ReadableStorage Medium 295 (e.g., via Network Interface 230).

The iSpot Server 200 may also comprise hardware supporting inputmodalities, Input 245, such as, for example, a touchscreen, a camera, akeyboard, a mouse, a trackball, a stylus, motion detectors, and amicrophone. Input 245 may also serve as Display 240, as in the case of atouchscreen display which also serves as Input 245, and which mayrespond to input in the form of contact by a finger or stylus with thesurface of Input 245. Input 245 and Display 240 may physically be partof iSpot Server 200 and/or may be a component(s) of another device, suchas of Imager-Sorter 100.

The iSpot Server 200 may also comprise or communicate via Bus 220 withiSpot Datastore 300, illustrated further in FIG. 3. In variousembodiments, Bus 220 may comprise a storage area network (“SAN”), a highspeed serial bus, and/or via other suitable communication technology. Insome embodiments, the iSpot Server 200 may communicate with the iSpotDatastore 300 via Network Interface 230. The iSpot Server 200 may, insome embodiments, include many more components than those shown in thisFigure. However, it is not necessary that all of these generallyconventional components be shown in order to disclose an illustrativeembodiment.

FIG. 3 is a functional block diagram of an exemplary iSpot ServerDatastore 300. The illustrated components of the iSpot Datastore 300 aredata groups used by routines and are discussed further herein in thediscussion of other of the Figures.

The data groups used by routines illustrated in FIG. 3 may berepresented by a cell in a column or a value separated from other valuesin a defined structure in a digital document or file. Though referred toherein as individual records or entries, the records may comprise morethan one database entry. The database entries may be, represent, orencode numbers, references to numbers and other values in other records,numerical operators, binary values, logical values, text, stringoperators, joins, conditional logic, tests, and similar.

FIG. 4 is a functional block diagram of an exemplary Smart TV 400computing device and some data structures and/or components thereof.Smart TV 400 comprises at least one Processing Unit 410, Smart TV Memory450, Display 440 and Input 445, all interconnected along with NetworkInterface 430 via Bus 420. Processing Unit 410 may comprise one or moregeneral-purpose Central Processing Units (“CPU”) 412 as well as one ormore special-purpose Graphics Processing Units (“GPU”) 414.

The components of Processing Unit 410 may be utilized by OperatingSystem 455 for different functions required by routines executed bySmart TV 400. Network Interface 430 may be utilized to form connectionswith Network 199 or to form device-to-device connections with othercomputers. Smart TV Memory 450 generally comprises a random accessmemory (“RAM”), a read only memory (“ROM”), and a permanent mass storagedevice, such as a disk drive or SDRAM (synchronous dynamic random-accessmemory). Smart TV Memory 450 stores program code for software routines,such as, for example, Viewing Data Collector 800, as well as, forexample, browser, email client and server routines, client applications,and database applications (discussed further below). Additional datagroups for routines, such as for a webserver and web browser, may alsobe present on and executed by the Smart TV 400. Webserver and browserroutines may provide an interface for interacting with the othercomputing devices illustrated in FIG. 1 or with other computing devicesnot illustrated in FIG. 1, for example, through webserver and webbrowser routines (which may serve and respond to data and information inthe form of webpages and html documents or files). The browsers andwebservers are meant to illustrate user- and machine-interface routinesgenerally, and may be replaced by equivalent routines for serving andrendering information to and in an interface in a computing device(whether in a web browser or in, for example, a mobile deviceapplication, or an API call to a server, a library, or the like).

In addition, Smart TV Memory 450 also stores Operating System 455. Thesesoftware components may be loaded from a non-transient Computer ReadableStorage Medium 495 into Smart TV Memory 450 of the computing deviceusing a drive mechanism (not shown) associated with a non-transientComputer Readable Storage Medium 495, such as a floppy disc, tape,DVD/CD-ROM drive, memory card, or other like storage medium. In someembodiments, software components may also or instead be loaded via amechanism other than a drive mechanism and Computer Readable StorageMedium 495 (e.g., via Network Interface 430).

The Smart TV 400 may also comprise hardware supporting input modalities,Input 245, such as, for example, a touchscreen, a camera, a keyboard, amouse, a trackball, a stylus, motion detectors, and a microphone. Input445 may also serve as Display 440, as in the case of a touchscreendisplay which also serves as Input 445, and which may respond to inputin the form of contact by a finger or stylus with the surface of Input445. Input 445 and Display 440 may physically be part of Smart TV 400and/or may be a component(s) of another device.

Smart TV 400 may also comprise or communicate via Bus 420 with Smart TVDatastore 500, illustrated further in FIG. 5. In various embodiments,Bus 420 may comprise a storage area network (“SAN”), a high speed serialbus, and/or via other suitable communication technology. In someembodiments, the Smart TV 400 may communicate with the Smart TVDatastore 500 via Network Interface 430. Smart TV 400 may, in someembodiments, include many more components than those shown in thisFigure. However, it is not necessary that all of these generallyconventional components be shown in order to disclose an illustrativeembodiment.

FIG. 5 is a functional block diagram of an exemplary Smart TV Datastore500. The illustrated components of the Smart TV Datastore 500 are datagroups used by routines and are discussed further herein in thediscussion of other of the Figures.

The data groups used by routines illustrated in FIG. 5 may berepresented by a cell in a column or a value separated from other valuesin a defined structure in a digital document or file. Though referred toherein as individual records or entries, the records may comprise morethan one database entry. The database entries may be, represent, orencode numbers, numerical operators, binary values, logical values,text, string operators, joins, conditional logic, tests, and similar.

FIG. 6 is a flowchart illustrating an exemplary embodiment of an AdHarvester 600 routine. Ad Harvester 600 may be executed by iSpot Server200 and/or by iSpot TV Monitor 110. Multiple television signal receiversmay be present in such devices and such devices or signal receiversthereof may be distributed across a large geographic area, such as inmultiple cities, in multiple states, and the like, connecting tomultiple different TV Distribution Media 180 to obtain linear televisionfrom many sources and to execute Ad Harvester 600 with respect to themultiple linear television sources.

Blocks 605 to 695 iterate over each TV Distribution Medium 180 to whichthe computer hardware executing the Ad Harvester 600 routine canconnect. Blocks 610 to 690 iterate over each “channel” which thecomputer hardware executing the Ad Harvester 600 routine can receive.“Channels” are commonly understood as dividing the communicationspectrum used by TV Distribution Medium 180, though “channels” are nowoften a logical division, not a physical or electro-magnetic division ofspectrum. For this reason, blocks 610 to 690 are labeled in relation toa “call sign” for each “channel”. “Call signs” are commonly assigned to“channels”; examples of “call signs” include NBC, ABC, CNN and the like.Call signs may be recorded in iSpot Datastore 300 as Call Sign 340records.

At block 615, the linear television received via the then-current CallSign 340 may encoded and/or transcoded from the source signal (which maybe analog or digital) obtained from the TV Distribution Medium 180. Theencoding and/or transcoding may be into or according to one or morecodecs and at a variety of frame or other rates.

At block 620, samples from the transcoded output of block 615 may beselected. For example, the samples may comprise 30 frames per second ofvideo and/or 7 chunks per second of audio, which may be a subset of thetranscoded data of block 615. Samples may comprise a full-resolutionand/or original linear television datastream, as originally broadcast.The samples and the encoded and/or transcoded data of block 615 and/or ahash or fingerprint thereof may be saved in, for example, Sample 385record or the like. Samples, hashes, or fingerprints may be referred toherein as a “representation”.

At block 625, Ad Harvester 600 may receive a program schedule for CallSign 340 in the TV Distribution Medium 180. The program schedule may bereceived from, for example, 3^(rd)Party Computer 150. The programschedule may be stored in, for example, Program Schedule 345 record.

At block 630, Ad Harvester 600 may identify the then-current show in theProgram Schedule 345 for Call Sign 340 at the then-current time. Theshow may be recorded in, for example, Show ID 350 record.

Blocks 635 to 685 iterate for each Show ID 350 record of block 630.Blocks 640 to 680 iterate for each Sample 385 of block 620. Theprocessing of blocks 640 to 680 may be in relation to video and/or audiosamples in Sample 385 records.

At block 645 a determination may be made whether the then-current Sample385 or a hash thereof matches a Sample 385 of or a hash thereofassociated with an existing iSpot Ad ID 320. This matching may also beperformed in relation to Advertisement Variations 387 prepared byReference Ad and Variation Module 1500. If not, then at block 1100, adetermination may be made regarding whether the Sample 385 meetscriteria for being an advertisement. This determination is discussedfurther in relation to FIG. 11.

If affirmative at block 1100, then at block 655 the start and stop ofthe advertisement may be determined. The start and stop of theadvertisement may be determined according to for example, characteristiclengths of advertisements in the TV Distribution Medium and Call Sign,when a scene change occurred in Samples 385 preceding the current Sample385, when a blank or black frame occurred in Samples 385 preceding thecurrent Sample 385, when a change in volume occurred relative to Samples385 preceding the current Sample 385, relative to the passage of time asmay have been evaluated at block 1155, relative to other advertisementsas may have been evaluated at block 1165, the length of other instancesof known and unknown content in which the Sample 385 occurs, andaccording to other criteria, including those evaluated in New AdIdentifier 1100.

At block 655 the Samples 385, such as the present Sample 385, and/or ahash, fingerprint, or representation for the advertisement may also bestored or may be labeled to be stored after all Samples 385 in theadvertisement have been processed.

At block 660, the advertiser in the advertisement may be identified,such as through identification of products, logos, trademarks, text,images, and the like which are associated with a known advertiser. Theidentified advertiser may be stored in, for example, an Advertiser 390record.

At block 665, the advertisement may be assigned an iSpot Ad ID 320 and,at block 670, which may follow block 645 if affirmative at block 645,data regarding the occurrence of the advertisement may be recorded, suchas in or in association with iSpot Ad ID 320, which data may compriseinformation such as a timestamp or timestamps for the advertisement(such as timestamps for different time zones), the iSpot Ad ID and theShow ID in which the advertisement occurred, the Pod number, commercialbreak number, or Ad Slot within the show (which may be recorded as Pod355 and/or as Ad Slot 395), the market in which the ad was shown (suchas a DMA 365), the Operator 160 and TV Distribution Media 180 of theshow and advertisement, a confidence score which may have been generatedin block 1100 to determine whether the Sample 385 is an advertisement orwhich may have been used in block 645 to determine that the Sample 385was a match with an existing iSpot Ad ID 320, the type of advertisementor the Ad Slot in which the advertisement appeared (as may be determinedby, for example, Ad Insertion Type Determiner 1000), the estimatedspending by the Advertiser 390 on the advertisement (“Estimated Spend”),a hash or representation of the Sample and/or of an AdvertisementVariation 387 and/or a Reference Advertisement 398 prepared and/oridentified in relation to the Sample (such as at block 1500), and thelike. The Estimated Spend may be determined according to, for example, aprocess such as that outlined in U.S. application Ser. No. 14/276,920,filed May 13, 2014.

At block 675, which may follow block 1100 if 1100 is not affirmative,the Sample 385 may be identified as not being an advertisement and maybe identified as a sample of a TV show, such as of Show ID 350 record ofblock 630 or otherwise according to Program Schedule 345, Call Sign 340and the then-current time. If not already performed, Show ID 350 may beassigned to the Sample 385 and the Sample 385 may be stored and/orhashed or fingerprinted and stored (which may be referred to herein as a“representation”). Information regarding the Sample 385 may also bestored, such as the time from the start of the show, a name of the show,the market (such as a DMA), the Operator, to TV Distribution Media, andthe like.

Following recordation of data regarding the advertisement or followingblock 675, Ad Harvester 600 may return to iterate over the next Sample385, Show, Call Sign, and TV Distribution Medium.

At block 1500, Ad Harvester 600 may execute Reference Ad and VariationModule 1500 to identify a reference advertisement corresponding to iSpotAd ID 320 and to generate variations of reference advertisements. Areference advertisement may be understood as a canonical or typical formof an advertisement associated with a particular iSpot Ad ID 320. Theidentified reference advertisement may be stored as, for example, one ormore Reference Advertisement 398 record(s). Reference Ad and VariationModule 1500 may also create variations of an advertisement, such asdifferent encodings, different resolutions, different aspect ratios andthe like. Advertisement variations may follow the format of variationsused by operators and TV networks. Advertisement variations may bestored as, for example, one or more Advertisement Variation 387 records.Advertisement Variation 387 may be fingerprint and included in“representations” or Sample 385 of advertisements, for comparisonrelative to samples from Smart TVs.

At block 699, Ad Harvester 600 may conclude or return to a process whichspawned Ad Harvester 600.

FIG. 7 is a flowchart illustrating an exemplary embodiment of a MediaPlan Determiner 700 routine. Media Plan Determiner 700 may be executedby, for example, iSpot Server 200. Media Plan Determiner 700 may beexecuted to determine the media plan for an advertisement. A media planfor an advertisement is a record of which shows an advertisementappeared in, on what days and at what times, in what Pods and Ad Slots,on what TV Distribution Media, in what markets, and the like.Advertisements are often placed by marketing companies with only generalguidance from the underlying advertiser; multiple parties may beinvolved in selecting which advertisements appear when and where. As aresult, the media plan for advertisements is seldom known in advance andprecise media plans developed after the fact—prior to the disclosureherein—may be expensive to compile and may be based on sampling andextrapolations, which can be prone to error.

Block 705 to 735 iterate for each advertisement assigned an iSpot Ad ID320 and with respect to which ad occurrence data was recorded, such asin block 670 of Ad Harvester 600.

At block 710, the ad occurrence data, such as of block 670 of AdHarvester 600, and the show information, such as of block 675 of AdHarvester, may be compiled or tabulated to determine a media plan forthen then-current iSpot Ad ID 320. The media plan may be stored as, forexample, Media Plan 315. A sample Media Plan 315 may contain columnssuch as, for example, Brand, Brand ID, Ad Title, iSpot Ad ID, Call Sign,Show Name, Show Episode, Show Type, Show Genre, Show Sub Genre, NewEpisode, Air Time Pacific/Central/Mountain/Eastern, Day of Week, DayPart, Pod and/or Slot Identifier, Airing Type (national, nationalsatellite, regional, etc.), Market (DMA), Platform (TV DistributionMedia), Operator, Duration, Parent iSpot Ad ID, Sample Hash ID,Industry, Sub Industry, Product Categories, Products, Estimated Spend,and the like.

At block 715, the Media Plan 315 across time zones and across Operators160 may be compared. This may be by comparison of Media Plans 315specific to each or within one Media Plan 315 which spans time zones andOperators 160.

At block 720, a determination may be made regarding whether for the sameshow, such as by Show ID 350, whether the same iSpot Ad ID 320 appearsin the same Ad Slot 395 within Show ID 350. If affirmative at block 720,then Ad Slot 395 for Show ID 350 may be categorized as a “national” AdSlot 395 and the iSpot Ad ID 320 may be categorized as a “national” ad.National Ad Slots are Ad Slots which are controlled by a party withnational reach, such as TV Network 185, and national Advertisements areadvertisements which are placed in national Ad Slots.

If negative at block 720, then at block 730 Ad Slot 395 for Show ID 350may be categorized as a “not national” Ad Slot or as a“regional/local/dynamic” Ad Slot. Regional Ad Slots are Ad Slots whichare sold or allocated to regional operators or advertising agencies tofill. Regional Ad Slots may be further categorized as “local” Ad Slotsif different advertisements are found in the same Ad Slot within aregion. Dynamic Ad Slots are regional or local Ad Slots which are filleddynamically by, for example, Operator 160 or an affiliate, and may bedynamically addressed to individual households or areas.

At block 735 Media Plan Determiner 700 may return to iterate over thenext iSpot Ad ID 320.

At block 799, Media Plan Determiner 700 may conclude or return to aprocess which spawned Media Plan Determiner 700.

FIG. 8 is a flowchart illustrating an exemplary embodiment of a ViewingData Collector 800 routine. Viewing Data Collector 800 may be executedby, for example, Smart TV 400. Viewing Data Collector 800 may be loadedin Smart TV 400 by, for example, a manufacturer or distributor of SmartTV 400 or by a party otherwise entitled to install software on Smart TV400.

At block 805, Viewing Data Collector 800 may receive audio and/or videosamples or hashes or fingerprints or another representation ofadvertisements which have been assigned an iSpot Ad ID 320, thecorresponding iSpot Ad IDs 320, samples, hashes, or fingerprints oranother representation of shows, and corresponding Show IDs 350. Theaudio and/or video samples, hashes, fingerprints, or representation ofboth advertisements and shows may be stored in Smart TV Datastore 500 asiSpot Sample 505; iSpot Ad IDs 320 may be stored in Smart TV Datastore500 as iSpot Ad IDs 510; Show IDs 350 may be stored in Smart TVDatastore 500 as Show IDs 515. The samples may be or comprise hashes orfingerprints of samples, which may be referred to herein as“representations”.

At block 810, Viewing Data Collector 800 may obtain a unique TVidentifier of the Smart TV 400, such as a MAC address or the like, andan IP Address utilized by the Smart TV 400. This data may be saved in orin association with, for example, a Smart TV Data 520 record.

At block 815, Viewing Data Collector 800 may obtain the DesignatedMarket Area (“DMA”) in which the Smart TV 400 is present. This may beobtained from a third party, such as 3^(rd) party Computer 150, who maymap the IP address of Smart TV 400 to a DMA and may provide thisinformation to Viewing Data Collector 800, such as in response to arequest for the same made by Viewing Data Collector 800.

Blocks 820 to 870 may iterate for the then-current channel or Call Signbeing received and rendered by Smart TV 400.

At block 825, Viewing Data Collector 800 may obtain the Call Sign of theTV Network 185 of the then-current channel. This may be obtained fromthe transmission over TV Distribution Media 180.

At block 830 a sample of content rendered by Smart TV 400 may beobtained from Smart TV 400 by Viewing Data Collector 800. The sample maybe, for example, 1 frame-per-second of video. This sample, hash,fingerprint, or representation thereof may be saved as, for example,Smart TV Sample 530.

Blocks 835 to 865 may iterate for each Smart TV Sample 530.

At block 840, a determination may be made regarding whether Smart TVSample 530 matches an existing iSpot Ad ID, a Show ID 515, or whether nomatch is obtained. This determination may involve a comparison of SmartTV Sample 530 to iSpot Sample 505, which iSpot Samples may be associatedwith a corresponding iSpot Ad IDs 510 and Show IDs 515. The comparisonmay be made by, for example, an Automated Content Recognition (“ACR”)algorithm executed by Smart TV 400 or by Viewing Data Collector 800,which ACR system (or the like) may use the Smart TV Sample 530 as areference.

If at block 840 the match was to a Show ID 515 or if there was no match,then at block 845, the matched Show ID 515 may be cross-referenced withShow Schedule 525 to confirm the match or to identify Show ID 515 if nomatch was determined. Show Schedule 525 may be obtained from atransmission over TV Distribution Media 180 and/or may obtained from orprovided by 3^(rd) Party Computer 150 or another party as a service. Atblock 850, the Show ID 515 may be returned.

If at block 840 the match was to an iSpot Ad ID 510, then at block 855the matching iSpot Ad ID 510 may be returned.

At block 860, the amount of time since the start of the show may bedetermined, such as relative to Show Schedule 525.

At block 865, Viewing Data Collector 800 may return to iterate over thenext Smart TV Sample 530, if any.

At block 870, Viewing Data Collector 800 may return to block 820 iterateover the next channel, if any.

At block 875, the information collected by Viewing Data Collector 800may be transmitted to iSpot Server 200 as, for example, Smart TV Data520 records, Show ID 515 records, and iSpot Ad ID 510 records. Thisinformation may further identify which iSpot Samples 505 were found, aswell as a confidence score relating to block 840 to 860.

At block 899, Viewing Data Collector 800 may conclude or return to aprocess which spawned Viewing Data Collector 800.

FIG. 9 is a flowchart illustrating an exemplary embodiment of a Smart TVData Collector 900 routine. Smart TV Data Collector 900 may be executedby, for example, iSpot Server 200.

At block 905, Smart TV Data Collector 900 may receive Smart TV Data 520,such as from Smart TV 400 and Viewing Data Collector 800.

At block 1000, Smart TV Data Collector 900 may execute Ad Insertion TypeDeterminer 1000, though Ad Insertion Type Determiner 1000 may beexecuted as an independent process, not as a subroutine. Ad InsertionType Determiner 1000 is discussed in relation to FIGS. 10A and 10B.

Blocks 910 to 980 iterate for each iSpot Ad ID in the Smart TV Data 520of block 905. Blocks 915 to 935 iterate for each airing of iSpot AD IDin the Smart TV Data 520 of block 905. Blocks 920 to 930 iterate foreach DMA in which occurred airings of iSpot AD ID.

At block 925, the number of impressions for each iSpot Ad ID 510 in orassociated with the Smart TV Data 520 in the DMA may be determined bydividing the number of reporting Smart TVs 400 in the Smart TV Data 520of block 905 by the number of tracked TVs (which may be either i) SmartTVs 400 which could potentially report or ii) all TVs) and multiplyingthe product of the foregoing by the number of television households inthe DMA.

Block 930 may return to block 920 to iterate over the next DMA. Block935 may return to block 915 to iterate over the next airing of iSpot AdID in Smart TV Data.

At block 940, Smart TV Data Collector 900 may determine the totaladvertisement impressions across geo-political units by summing, forexample, the ad impressions by DMA determined in block 925. This willdetermine the advertisement impressions for “national” advertisements(those placed in national Ad Slots 395) as well as “regional”advertisements (advertisements placed in regional Ad Slots 395—thenational/regional categorization having been made by, for example, MediaPlan Determiner 700).

At block 945, the Gross Rating Points (“GRP”) may determined as thereach of an iSpot Ad ID (expressed as a percentage of the totalpopulation) multiplied by the frequency or average frequency of theoccurrence of the advertisement associated with the iSport Ad ID. TheGRP may be saved as, for example, GRP 330 records.

At block 950, Smart TV Data Collector 900 may obtain demographics forthe Smart TVs 400 providing data at block 905. At block 955, Smart TVData Collector 900 may obtain census data relative to the populationpossessing Smart TVs 400 which provided data at block 905.

At block 960, Smart TV Data Collector 900 may calibrate the devicedemographics of block 950 relative to the census data of block 955.

Blocks 965 to 975 iterate for each target audience in the totalpopulation, such as an age range, a geographic area, a gender, and thelike, in the total population.

At block 970, Smart TV Data Collector 900 may determine the TargetRating Points (“TRP”) by multiplying the GRP of block 935 by theestimated percentage of the target audience in the gross audience (ortotal population). The TRP may be saved as, for example, TRP 335records.

Block 975 may return to block 965 to iterate over the next targetaudience, if any.

Block 980 may return to block 910 to iterate over the next iSpot Ad ID.

At block 985, Smart TV Data Collector 900 may connect Media RenderingDevices 120 to Smart TVs 400, such as according to IP Address or otherinformation, to determine Media Rendering Devices 120 and Smart TVs 400which occupy a common location, so that data from one can be ascribed tothe other.

At block 999, Smart TV Data Collector 900 may conclude or return to aprocess which spawned it.

FIGS. 10A and 10B are a flowchart illustrating an exemplary embodimentof an Ad Insertion Type Determiner 1000 routine. Ad Insertion TypeDeterminer 1000 may be executed by iSpot Server 200 within Smart TV DataCollector 900 as a subroutine or as an independent process. Ad InsertionType Determiner 1000 determines a type of advertisement insertion foradvertisements which have been given an iSpot Ad ID 320, relative to theadvertisement and/or an Ad Slot into which an advertisement may beinserted.

Blocks 1004 to 1080 iterate for each show, such as by Show ID 350, inthe Smart TV Data 380 received at, for example, block 905 in Smart TVData Collector 900. Blocks 1008 to 1076 iterate for each iSpot Ad IDreceived at, for example, block 905 in Smart TV Data Collector 900.

At block 1012, a determination may be made regarding whether the SmartTV content and the then-current iSpot Ad ID tracks the Media Plan 315determined by Media Plan Determiner 700.

If affirmative at block 1012, then at block 1044, a determination may bemade regarding whether there is a time difference between the Smart TVcontent and the Media Plan 315, such as according to a timestamp. Ifnegative at block 1044, then at block 1048 the iSpot Ad ID in the Showmay be categorized as “live”, meaning that it was rendered by thereporting Smart TV 400 in real time. If affirmative at block 1044, thenat block 1052 a determination may be made regarding whether the timedifference is greater than three days. If negative at block 1052, thenat block 1056, the iSpot Ad ID in the Show may be categorized as“timeshifted, up to three days.” If affirmative at block 1052, then atblock 1060, then iSpot Ad ID in Show may be categorized as “timeshifted,greater than three days.”

At block 1068, a determination may be made, for advertisements in anon-national Ad Slot and for a single Operator, regarding whether or notthe advertisement insertion follows a pattern for local, regional, ordynamic advertisement insertion. For example, a single Operator may showthe same advertisement across a region, such as across an MTA (in whichcase the advertisement and/or Ad Slot may be categorized as “regional”),or may show different advertisements within a region (in which case theadvertisement and/or Ad Slot may be categorized as “local”), or may showdifferent advertisements to many different viewers without regard togeographic proximity (in which case the advertisement and/or Ad Slot maybe categorized as “dynamic”). Depending on the determination at block1068, the advertisement and/or Ad Slot and/or advertisement insertiontype may be categorized as “locally” or “regionally inserted”, such asat block 1072, or the advertisement and/or Ad Slot may be categorized as“dynamically inserted”, such as at block 1064.

If negative at block 1012, then, in FIG. 10B at block 1020 adetermination may be made regarding whether the Show in which the Ad IDoccurred is known. If negative at block 1020, then at block 1024, the AdSlot in which the iSpot Ad ID occurred may be categorized as “other”.

If affirmative at block 1020, then at block 1028, for the Show in whichthe iSpot Ad ID occurred, the lengths of blocks of advertisements in theShow, the position of advertisements in the Show, and othercharacteristics may be measured. Different TV Distribution Media mayhave different lengths of blocks of advertisements in Shows, positionsof advertisements in Shows, and other characteristics. At block 1032,the TV Distribution Media of the Show and Advertisement may be assignedas a type, such as on-demand, OTT, or Internet. At block 1036, thesource may be identified, such as according to information in the SmartTV Data received, for example, at block 905. The source may a subset ofor a particular provider within the type identified at block 1032, suchas an Operator (such as Comcast, Timewarner, DirecTV, and the like) oran OTT provider (such as Amazon, Hulu, Netflix, and the like), or anInternet provider (such as YouTube). At block 1040, the sourceidentified at block 1036 may be assigned as a sub-type. At circle “C”,FIG. 10B may return to block 1076.

At block 1076, Ad Insertion Type Determiner 1000 may return to block1008 to iterate over the next iSpot Ad ID. At block 1080, Ad InsertionType Determiner 1000 may return to block 1004 to iterate over the nextShow.

At block 1099, Ad Insertion Type Determiner 1000 may conclude or mayreturn to a process which spawned it.

FIG. 11 is a flowchart illustrating an exemplary embodiment of a New AdIdentifier 1100 routine. New Ad Identifier 1100 determines whether aSample 385 which does not match an existing iSpot Ad ID 320 is anadvertisement. New Ad Identifier 1100 may apply criteria for making thisdetermination. New Ad Identifier 1100 may utilize a scoring system whichapplies a score (or scores) to various criteria and may then determinethat Sample 385 is an advertisement if the total score is above athreshold; equivalent systems for evaluating a list of criteria may beutilized. A list of examples of criteria for being an advertisement arelisted in FIGS. 11A and 11B. A different set of criteria may be utilizedand the criteria may be utilized in a different order. Evaluation of thecriteria may be terminated upon the occurrence of an event or adispositive criteria.

For example, at block 1105 a determination may be made regarding whetherthe Sample 385 represents a scene change relative to a chronologicallypreceding Sample 385. The scene change evaluation may be based on achange in the video data. This evaluation may be performed by evaluatingencoding of frames. For example, a Sample 385 which uses a precedingframe as a reference for motion-vector based compression may not beconsidered a scene change. This evaluation may also utilize a histogramof pixels in Sample 385 and a preceding Sample 385. An “earth moverdistance” or other similar algorithm may also be utilized. Ifaffirmative, then at block 1110, the advertisement score for Sample 385may be incremented.

For example, at block 1115 a determination may be made regarding whetherSample 385 is preceded by a blank or black frame. If affirmative, thenat block 1120, the advertisement score for Sample 385 may beincremented.

For example, at block 1125 a determination may be made regarding whetherthere is a change of volume in the Sample 385 relative to a precededSample. If affirmative, then at block 1130, the advertisement score forSample 385 may be incremented.

For example, at block 1135 a determination may be made regarding whethera “ticker” or scrolling text in a preceding Sample 385 is not present inthe then-current Sample 385. If affirmative, then at block 1140, theadvertisement score for Sample 385 may be incremented.

For example, at block 1145 a determination may be made regarding whethera “ticker” or scrolling text in a preceding Sample 385 is not present inthe then-current Sample 385. If affirmative, then at block 1140, theadvertisement score for Sample 385 may be incremented.

For example, at block 1155 a determination may be made regarding whetheran amount of time has elapsed during the current Show, since the startof the current Show, or since the last advertisement in the currentShow, which amount of time is associated with an advertisement. Ifaffirmative, then at block 1160, the advertisement score for Sample 385may be incremented.

For example, at block 1165 a determination may be made regarding whetherthe current Sample 385, or a time range of Samples around current Sample385, is preceded, followed by, or bracketed by (on both sides) by aSample which matches an existing iSpot Ad ID 320. If affirmative, thenat block 1170, the advertisement score for Sample 385 may beincremented.

For example, at block 1175 a determination may be made regarding whetherthe current Sample 385 occurs elsewhere, such as in other broadcasts byother Call Signs 340 or on other Channels 310, or on other Networks 305.If affirmative, then at block 1180, the advertisement score for Sample385 may be incremented.

At block 1185 a determination may be made regarding whether the totalscore for the current Sample 385 is above a threshold. If it is, then atblock 1190 the current Sample 385 may be classified as an advertisementand New Ad Identifier 1100 routine may, for example, return to block 655of FIG. 6. If it is not, then at block 1195 the current Sample 385 maybe classified as other than an advertisement and New Ad Identifier 1100routine may, for example, return to block 675 of FIG. 6. New AdIdentifier 1100 routine may also provide that scores close to but notover the threshold may be evaluated by a human.

FIG. 12 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a View Rate Module 1200. View Rate Module 1200receives a fingerprint or iSpot Ad ID 320 and a Unique TV ID 325,matches it to an iSpot Ad ID 320, and adds it to a View Rate determiningseries for all such data. The series is indexed or organized by iSpot AdID 320 and Unique TV ID 325. Overlap and Behavior Module 1300 may beexecuted to determine View Rate 396 for the Unique TV ID 325 and iSpotAd ID 320, as well as the advertisement type and behavior of a user ofthe television with Unique TV ID 325. Benchmark Module 1400 may beexecuted to determine current View Rate benchmarks relative to extrinsicstandards, such as average view rate for all advertisements, all ads bybroadcaster and daypart, by network, and locale.

At block 1205, View Rate Module 1200 receives a fingerprint or iSpot AdID 320 and Unique TV ID 325 from a Smart TV.

At decision block 1210, View Rate Module 1200 determines whetherfingerprint or iSpot Ad ID 320 matches an existing iSpot Ad ID 320. Ifnegative or equivalent, View Rate Module 1200 may return to block 1205.If affirmative or equivalent, View Rate Module 1200 may add iSpot Ad ID320 to a series of records in a datastructure. The datastructure may beorganized and/or indexed by iSpot Ad ID 320 and Unique TV ID 325. Thedatastructure may be stored as, for example, one or more View RateSeries 399 records.

Opening loop block 1220 to closing loop block 1235 may iterate over alliSpot Ad ID 320 in View Rate Series 399. Opening loop block 1225 toclosing loop block 1230 may iterate over all Unique TV ID 325 in ViewRate Series 399. Together, this allows determination of View Rate forspecific advertisements, by specific televisions, to be determined.

At block 1300, Overlap and Behavior Module 1300 may be executed todetermine View Rate 396 for the Unique TV ID 325 and iSpot Ad ID 320, aswell as the advertisement type and behavior of a user of the televisionwith Unique TV ID 325.

At block 1400, Benchmark Module 1400 may be executed to determinecurrent View Rate benchmarks relative to extrinsic standards, such asaverage view rate for all advertisements, all ads by broadcaster anddaypart, by network, and locale, as well as standards intrinsic to anadvertisement, such as an average View Rate 396 for an advertisement,including for dayparts, broadcast network, locale, and the like.

At block 1240, View Rate Module 1200 may output View Rate 396 values,including outputting View Rate 396 values relative and/or inconjunctions with Benchmark 397 values, such as by outputting suchvalues in graphs and other graphical forms.

At block 1299, View Rate Module 1200 may conclude and/or return to aprocess, routine, or module which may have called it.

FIG. 13A is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of a first portion of an Overlap and BehaviorModule 1300. FIG. 13B is a flowchart illustrating an exemplaryembodiment and/or algorithmic structure of a second portion of anOverlap and Behavior Module 1300, continuing the flowchart of FIG. 13A.Overlap and Behavior Module 1300 may be executed by, for example iSpotServer 200. Overlap and Behavior Module 1300 iterates over View RateSeries 399 for an iSpot Ad ID 320 and for a Unique TV ID 325.

At block 1305, Overlap and Behavior Module 1300 may match achronologically recorded set of fingerprints associated with iSpot Ad ID320 and Unique TV ID 325 in View Rate Series 399 to Sample 385 recordsor another record associated with an iSpot Ad ID 320, which records maybe stored and/or identified as one or more “Reference Advertisement 398”record. Reference Advertisement 398 may be understood as a canonicalform of an advertisement associated with a particular iSpot Ad ID 320.This matching may be performed retrospectively, over a set offingerprints which at least have the potential to match with ReferenceAdvertisement 398 record, such as after View Rate Series 399 has aged,such as more than 3 minutes, 30 minutes, one hour, one day, or the like.

At decision block 1310, Overlap and Behavior Module 1300 may determinewhether there is a discontinuity between Reference Advertisement 398 andfingerprints associated with iSpot Ad ID 320 and Unique TV ID 325 inView Rate Series 399. The determination may require that thediscontinuity exceed a threshold, such as a threshold to address anerror-rate or sample-rate in one or both of the fingerprints in ViewRate Series 399 and/or in Reference Advertisement 398. The discontinuitymay be, for example, a break, missing fingerprints, or a differencebetween fingerprints in View Rate Series 399 and Reference Advertisement398.

At block 1315, Overlap and Behavior Module 1300 may determine thepercentage which is the same or the percentage which is differentbetween fingerprints associated with iSpot Ad ID 320 and Unique TV ID325 in View Rate Series 399 and Reference Advertisement 398.

Opening loop block 1320 to closing loop block 1375 may iterate over thepercentage which is not the same.

At block 1325, Overlap and Behavior Module 1300 may determine therelative temporal location of the discontinuity between fingerprintsassociated with iSpot Ad ID 320 and Unique TV ID 325 in View Rate Series399 and Reference Advertisement 398. This temporal location may beidentified as a percentage of the advertisement which was rendered. Forexample, the relative temporal location of the discontinuity may occurin a first, second, third, or fourth quartile of Reference Advertisement398.

At block 1327, Overlap and Behavior Module 1300 may determine a drop-offpoint for the fingerprints associated with iSpot Ad ID 320 and Unique TVID 325 in View Rate Series 399 relative to Reference Advertisement 398.A drop-off point comprises a time, relative to the start of rendering ofthe television advertisement, when rendering of the televisionadvertisement (as shown by fingerprints associated with iSpot Ad ID 320and Unique TV ID 325 in View Rate Series 399) is discontinued, before anend of the reference television advertisement. Drop-off point may bedetermined relative to broadcasters, dayparts, broadcaster and daypart,by locale, by locale and daypart, and the like. Drop-off point resultsmay be stored in, for example, one or more Drop-Off Point 388 records.

At decision block 1330, Overlap and Behavior Module 1300 may determinewhether the discontinuity occurs at the start of Reference Advertisement398. This may indicate that the viewer did not see the beginning of theadvertisement. Certain advertisers and/or marketers may not want to“count” a view in View Rate 396 for an advertisement if the viewer didnot see the beginning of the advertisement. If affirmative or equivalentat decision block 1330, then at block 1335, Overlap and Behavior Module1300 may flag or otherwise label the fingerprints associated with iSpotAd ID 320 and Unique TV ID 325 in View Rate Series 399 as being a “noview” or otherwise may not count such rendering in View Rate 396 for anadvertisement. After block 1335, FIG. 13A may then continue at location“A” in FIG. 13B.

At block 1100, if not already performed, Overlap and Behavior Module1300 may perform Ad Insertion Type Determiner 1000 to determine theinsertion type for the overall advertisement, such as whether it islive, timeshifted, dynamic, local/regional, on-demand, OTT, internet.

At decision block 1340, Overlap and Behavior Module 1300 may determinewhether the discontinuity between the fingerprints associated with iSpotAd ID 320 and Unique TV ID 325 in View Rate Series 399 and ReferenceAdvertisement 399 is consistent with an insert into ReferenceAdvertisement 399. For example, certain advertisements allow regional orlocal insertion into the advertisements, such as a list of local cardealers or the like. Such insertions may come, for example, at the endor in another location in an advertisement and may be of a fixedduration, such as three, five or ten seconds. Consistency with an insertmay be determined with respect to characteristics of inserts inReference Advertisement 399 or may be determined with respect tocharacteristics of inserts, generally, such as that inserts often occurat the end of advertisements.

If affirmative or equivalent at decision block 1340, then at block 1345,Overlap and Behavior Module 1300 may flag the discontinuity as an insertinto Reference Advertisement 399, in which case the discontinuity may beignored. Ignoring the discontinuity may mean that the ReferenceAdvertisement 399 is effectively treated as being shorter than it is,when viewed with the insert. At block 1350, Overlap and Behavior Module1300 may update Reference Advertisement 399 or another record toindicate that it has been identified as having an insert.

At block 1355, Overlap and Behavior Module 1300 may label thefingerprints associated with iSpot Ad ID 320 and Unique TV ID 325 inView Rate Series 399 to be credited toward View Rate 396 for the iSpotAd ID 320, according to percentage which is the same (or different) and,for example, according to the relative temporal location of thediscontinuity determined at block 1325 (such as according to a firstquartile, second quartile, third quartile, or fourth quartile) and thedrop-off point of block 1327. A daypart for the fingerprints associatedwith iSpot Ad ID 320 and Unique TV ID 325 in View Rate Series 399 mayalso be determined at this block, such as according to when records forwhen fingerprints associated with iSpot Ad ID 320 and Unique TV ID 325in View Rate Series 399 were recorded, relative to the location and timezone of the reporting Unique TV ID 325. The broadcaster and/or localereported by or determined for Unique TV ID 325 may also be obtained andlabeled, flagged, or indexed at this block, such that Benchmark Module1400 may determine the average view rate for the advertisement acrossall reporting TVs, further relative to broadcasters, dayparts, localesand the like.

After block 1355, FIG. 13A may then continue at location “B” in FIG.13B.

At decision block 1360, Overlap and Behavior Module 1300 may determinewhether the discontinuity is followed by content on the same or adifferent channel. This may be determined according to, for example,information received by Smart TV Data Collector 900 from Viewing DataCollector 800.

If decision block 1360 indicates that the following content is on adifferent channel, then the discontinuity may be flagged or labeled as achannel change. If decision block 1360 indicates that the followingcontent is on the same channel, then the discontinuity may be flagged orlabeled as a fast forward.

At done block 1399, Overlap and Behavior Module 1300 may conclude and/orreturn to a process which spawned it.

FIG. 14 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of Benchmark Module 1400. Benchmark Module 1400may be executed by, for example, iSpot Server 200. Benchmark Module 1400may be executed to determine current View Rate benchmarks relative toextrinsic standards, such as average view rate for all advertisements,all ads broadcast by a broadcaster, broadcast in a daypart, broadcast bynetwork, and broadcast in a locale, as well as standards intrinsic to anadvertisement, such as an average View Rate 396 for an advertisement,average View Rate 396 for the advertisement by daypart, broadcastnetwork, locale, and the like. Benchmark Module 1400 may also determinean average completion rate and peak drop-off point for an advertisement.

At block 1405, Benchmark Module 1400 may determine the current averageof View Rate 396 records for each advertisement associated with an iSpotAd ID 320. The average view rate may be determined relative tobroadcasters, dayparts, broadcaster and daypart, by locale, by localeand daypart, and the like.

At block 1410, Benchmark Module 1400 may determine the averagecompletion rate for each advertisement associated with an iSpot Ad ID320. The average completion rate may be determined relative tobroadcasters, dayparts, broadcaster and daypart, by locale, by localeand daypart, and the like. The average completion rate of the televisionadvertisement comprises a percentage of renderings in which the renderedtelevision advertisement was rendered without interruption, relative toall reporting televisions. The average completion rate may be determinedby using Drop-Off Point 388 records. Average completion rate results maybe stored as, for example, one or more Completion Rate 389 records.

At block 1415, Benchmark Module 1400 may, for each advertisementassociated with an iSpot Ad ID 320, plot Drop-Off Point 388 records anddetermine one or more local maxima or peaks. Peak drop-off point may bedetermined for each advertisement relative to broadcasters, dayparts,broadcaster and daypart, by locale, by locale and daypart, and the like.These results may also be stored in one or more Drop-Off Point 388records.

At block 1420, Benchmark Module 1400 may determine the current averageof View Rate 396 records for all advertisements. This may be determinedto include or reveal such information organized by advertisements bybroadcaster, by daypart, by broadcaster and daypart, by industry, byproduct, product type, product competitor, and the like.

At done block 1499, Benchmark Module 1400 may conclude and/or may returnto a process which may have spawned it.

FIG. 15 is a flowchart illustrating an exemplary embodiment and/oralgorithmic structure of Reference Advertisement and Variation Module1500. Reference Advertisement and Variation Module 1500 may be executedby, for example, iSpot Server 200, whether independently (not as asubroutine or submodule) or as a module or routine called by anotherprocess, module, or routine. Reference Advertisement and VariationModule 1500 may be executed to identify a reference advertisementcorresponding to iSpot Ad ID 320 and to generate variations of referenceadvertisements. A reference advertisement may be understood as acanonical or typical form of an advertisement associated with aparticular iSpot Ad ID 320. The identified reference advertisement maybe stored as, for example, one or more Reference Advertisement 398record(s). Reference Ad and Variation Module 1500 may also createvariations of an advertisement, such as different encodings, differentresolutions, different aspect ratios and the like. Advertisementvariations may follow the format of variations used by operators and TVnetworks. Advertisement variations may be stored as, for example, one ormore Advertisement Variation 387 records. Advertisement Variation 387may be fingerprint and included in “representations” or Sample 385 ofadvertisements, for comparison relative to samples from Smart TVs.

Opening loop block 1505 to closing loop block 15015 may iterate overiSpot Ad ID 320, or at least iSpot Ad ID 320 which are not yetassociated with a Reference Advertisement 398.

At block 1510, Reference Advertisement and Variation Module 1500 mayidentify a reference advertisement corresponding to a then-current iSpotAd ID 320. An identified reference advertisement may be, for example, afirst set of Sample 385 records associated with a then-current iSpot AdID 320, a most common set of Sample 385 records associated with athen-current iSpot Ad ID 320, a set of Sample 385 records associatedwith a selected Network 305, a set of Sample 385 records with fewesterrors or fewest missing frames, and/or a combination of these factorsor the like. An identified reference advertisement and/or Samples 385records thereof may be stored as or associated with, for example, one ormore Reference Advertisement 398 records.

At closing loop block 1515, Reference Advertisement and Variation Module1500 may iterate over a next iSpot Ad ID 320 and/or may proceed.

Opening loop block 1520 to closing loop block 1560 may iterate over eachReference Advertisement 398 records or at least those ReferenceAdvertisement 398 records which have not previously had variationsgenerated in relation thereto.

A decision block 1525, Reference Advertisement and Variation Module 1500may determine if the Reference Advertisement 398 is known to or has beenobserved to be broadcast by one or more TV Network 185, Network 305,and/or Channel 310 known to modify advertisements. For example, “ESPN”may be known to be a Network 305 and/or Channel 310 which is known orwhich has been observed to broadcast advertisements in a modifiedformat.

If affirmative or equivalent at decision block 1525, then opening loopblock 1530 to closing loop block 1555 may iterate over each TV Network185, Network 305, and/or Channel 310 known to modify advertisements,with respect to the then-current Reference Advertisement 398.

At block 1535, Reference Advertisement and Variation Module 1500 mayobtain template(s) for modification of advertisements by the TV Network185, Network 305, and/or Channel 310. For example, TV Network 185,Network 305, and/or Channel 310 may modify advertisements incharacteristic ways which follow or can be described according totemplates. For example, modification templates may comprise graphical,encoding, and/or another modification. For example, graphicalmodifications may comprise a reduced display area of, a cropping of, achanged aspect ratio of an “original” Reference Advertisement 398. Thegraphical modification may be further comprise an insert area, whereinthe insert area may be an area in which a party inserts text, includingstatic or scrolling text (including a “ticker” of scrolling text),credits, news, advertisements, social media content, programinformation, or the like. The insert area may comprise images, includingstatic images and/or video. The insert area may be above, below, orbeside Reference Advertisement 398. The reduced display area mayaccommodate the insert area and/or the insert area may be an overlay oran underlay. There may be no or more than one insert area in a template.

An encoding modification may comprise, for example, a different encodingformat, a different packet format, a different bitrate, or the like.

At block 1540, Reference Advertisement and Variation Module 1500 maymodify Reference Advertisement 398 according to the template(s) of thethen current TV Network 185, Network 305, and/or Channel 310. Withrespect to insert area(s), the template may substitute a blank area, acharacteristic text or image or a text or image. The blank area, acharacteristic text or image or a text or image may serve as asubstitute and/or may signal the presence of an insert area.

At block 1545, Reference Advertisement and Variation Module 1500 maycreate a hash of modification(s) of Reference Advertisement 398 createdat block 1540. The hash may correspond to a sample hash created at, forexample, block 670 of FIG. 6.

At block 1550, Reference Advertisement and Variation Module 1500 maystore the modified Reference Advertisement 398 and/or a hash thereof iniSpot Server Datastore 300 as, for example, one or more AdvertisementVariation 387 records. Advertisement Variation 387 records may beassociated with Reference Advertisement 398 records.

At done block 1599, Reference Advertisement and Variation Module 1500may conclude and/or may return to a process which may have spawned it.

The above Detailed Description of embodiments is not intended to beexhaustive or to limit the disclosure to the precise form disclosedabove. While specific embodiments of, and examples are described abovefor illustrative purposes, various equivalent modifications are possiblewithin the scope of the system, as those skilled in the art willrecognize. For example, while processes or blocks are presented in agiven order, alternative embodiments may perform routines havingoperations, or employ systems having blocks, in a different order, andsome processes or blocks may be deleted, moved, added, subdivided,combined, and/or modified. While processes or blocks are at times shownas being performed in series, these processes or blocks may instead beperformed in parallel, or may be performed at different times. Further,any specific numbers noted herein are only examples; alternativeimplementations may employ differing values or ranges.

Following are examples of the foregoing disclosure.

Example 1

An apparatus for determining a view rate of a television advertisement,comprising: a computer processor and a memory; a view rate determiningmodule coupled to the computer processor, the view rate determiningmodule to determine the view rate of the television advertisement,wherein to determine the view rate of the television advertisement, theview rate determining module is to: receive from a remote television astream of fingerprints of television content rendered by the remotetelevision, determine a reference television advertisement in the streamof fingerprints, determine a rendered span of the reference televisionadvertisement in the stream of fingerprints, and determine the view rateof the television advertisement according to the rendered span of thereference television advertisement in the stream of fingerprints.

Example 2

The apparatus according to Example 1, wherein to determine the renderedspan of the reference television advertisement in the stream offingerprints, the view rate determining module is to determine apercentage of the reference television advertisement corresponding tothe stream of fingerprints.

Example 3

The apparatus according to Example 2, wherein the percentage of thereference television advertisement are bucketized into viewingquartiles.

Example 4

The apparatus according to Example 3 wherein the quartiles comprise afirst quartile for 0 to 25 percent of the reference televisionadvertisement rendered, a second quartile for 26 to 50 percent of thereference television advertisement rendered, a third quartile for 51 to75 percent of the reference television advertisement rendered, and aforth quartile for 76 to 100 percent of the reference televisionadvertisement rendered.

Example 5

The apparatus according to Example 1, wherein to determine the renderedspan of the reference television advertisement in the stream offingerprints, the view rate determining module is to determine where therendered span of the reference television advertisement in the stream offingerprints begins relative to a start of the reference televisionadvertisement.

Example 6

The apparatus according to Example 1, wherein to determine the view rateof the television advertisement, the view rate determining module isfurther to correct for a portion of the rendered span of the referencetelevision advertisement that does not match a portion of the referencetelevision advertisement.

Example 7

The apparatus according to Example 6, wherein to correct for the portionof the rendered span of the reference television advertisement that doesnot match the portion of the reference television advertisementcomprises to determine that the portion of the rendered span is aninsert inserted into a specific portion of the reference televisionadvertisement.

Example 8

The apparatus according to Example 7, wherein to correct for the portionof the rendered span of the reference television advertisement that doesnot match the reference television advertisement comprises to subtractthe portion of the rendered span of the reference televisionadvertisement from the reference television advertisement.

Example 9

The apparatus according to Example 6, wherein to correct for the portionof the rendered span of the reference television advertisement that doesnot match the reference television advertisement comprises to determinethat the portion of the rendered span of the television advertisement isfollowed in the stream of fingerprints by a television content, whereinthe television content is one of chronologically continuous ordiscontinuous relative to an original broadcast.

Example 10

The apparatus according to Example 9, wherein the television content ischronologically continuous and is determined to have been broadcast by asame broadcast network, relative to a broadcast network which broadcastthe stream of fingerprints comprising the rendered span of the referencetelevision advertisement.

Example 11

The apparatus according to Example 9, wherein the television content ischronologically continuous and is determined to have been broadcast by adifferent broadcast network, relative to a broadcast network whichbroadcast the stream of fingerprints comprising the rendered span of thereference television advertisement, indicating a change of channel.

Example 12

The apparatus according to Example 9, wherein the television content isdetermined to be chronologically discontinuous relative to the stream offingerprints comprising the rendered span of the reference televisionadvertisement, indicating a fast forward.

Example 13

The apparatus according to Example 1, wherein the view rate determiningmodule is further to characterize the television advertisement as atleast one of live, time shifted, or on-demand.

Example 14

The apparatus according to Example 1, wherein the view rate determiningmodule is further to determine an average of the view rate of thetelevision advertisement by more than one television.

Example 15

The apparatus according to Example 14, wherein the average of the viewrate of the television advertisement by more than one television isfurther averaged across at least one of a broadcast network, a locale,or a daypart.

Example 16

The apparatus according to Example 14, further comprising determining anaverage completion rate of the television advertisement, wherein theaverage completion rate of the television advertisement comprises apercentage of renderings in which the rendered television advertisementwas rendered without interruption.

Example 17

The apparatus according to Example 14, wherein the average view rate isoutput relative to, in conjunction with, or as part of a benchmark.

Example 18

The apparatus according to Example 17, wherein the benchmark comprisesat least one of: an average view rate for all television advertisements;an average view rate for all television advertisements of an industry;an average view rate for all television advertisements of a productadvertised in the television advertisement; a view rate of a broadcastadvertisement associated with a competitor of the product advertised inthe television advertisement; an average view rate of all broadcastadvertisements associated with a competitor of the product advertised inthe television advertisement; a view rate of all televisionadvertisements for all broadcast networks; or any combination of theabove.

Example 19

The apparatus according to Example 14, wherein the view rate determiningmodule is further to determine a peak drop-off point for the televisionadvertisement.

Example 20

The apparatus according to Example 19, wherein a drop-off pointcomprises a time, relative to the start of the television advertisement,when rendering of the television advertisement is discontinued before anend of the reference television advertisement and wherein the peakdrop-off point comprises the peak of a set of drop-off points by themore than one television.

Example 21

An apparatus for preparing modified reference advertisements,comprising: a computer processor and a memory; a datastore comprisingreference advertisements; an ad modification module coupled to thecomputer processor, the ad modification module to modify referenceadvertisements, wherein ad modification module is to: identify areference advertisement broadcast by a broadcast network in a modifiedformat; create a modification of the reference advertisement accordingto the modified format; store the modification of the referenceadvertisement in the datastore of reference advertisements inassociation with reference advertisement.

Example 22

The apparatus according to Example 21, wherein the modified formatcomprises a least one of a graphical modification and an encodingmodification.

Example 23

The apparatus according to Example 22, wherein the graphicalmodification comprises an insert area.

Example 24

The apparatus according to Example 23, wherein the graphicalmodification comprises a reduced display area of the referenceadvertisement, wherein the reduced display area of the referenceadvertisement accommodates the insert area.

Example 25

The apparatus according to Example 24, wherein the insert area comprisesat least one of text or graphics and wherein the insert area is locatedabove, below, or beside the reference advertisement.

Example 26

The apparatus according to Example 22, wherein the graphicalmodification comprises an aspect ratio change.

Example 27

The apparatus according to Example 22, wherein the graphicalmodification comprises an overlay or underlay.

Example 28

The apparatus according to Example 21, further comprising an adharvesting module coupled to the computer processor, the ad harvestingmodule to identify advertisements, wherein identify advertisements, thead harvesting module is to receive a set of viewing data from a smartTV, the set of viewing data comprising an sample of broadcast contentreceived by the smart TV, and determine that the sample of broadcastcontent corresponds to the modification of the reference advertisement.

Example 29

A computer implemented method for determining a view rate of atelevision advertisement, comprising: receiving from a remote televisiona stream of fingerprints of television content rendered by the remotetelevision, determining a reference television advertisement in thestream of fingerprints, determining a rendered span of the referencetelevision advertisement in the stream of fingerprints, and determiningthe view rate of the television advertisement according to the renderedspan of the reference television advertisement in the stream offingerprints.

Example 30

The method according to Example 29, wherein determining the renderedspan of the reference television advertisement in the stream offingerprints comprises determining a percentage of the referencetelevision advertisement corresponding to the stream of fingerprints.

Example 31

The method according to Example 30, wherein the percentage of thereference television advertisement are bucketized into viewingquartiles.

Example 32

The method according to Example 31 wherein the quartiles comprise afirst quartile for 0 to 25 percent of the reference televisionadvertisement rendered, a second quartile for 26 to 50 percent of thereference television advertisement rendered, a third quartile for 51 to75 percent of the reference television advertisement rendered, and aforth quartile for 76 to 100 percent of the reference televisionadvertisement rendered.

Example 33

The method according to Example 29, wherein determining the renderedspan of the reference television advertisement in the stream offingerprints comprises determining where the rendered span of thereference television advertisement in the stream of fingerprints beginsrelative to a start of the reference television advertisement.

Example 34

The method according to Example 29, further comprising correcting for aportion of the rendered span of the reference television advertisementthat does not match a portion of the reference television advertisement.

Example 35

The method according to Example 34, wherein correcting for the portionof the rendered span of the reference television advertisement that doesnot match the portion of the reference television advertisementcomprises determining that the portion of the rendered span is an insertinserted into a specific portion of the reference televisionadvertisement.

Example 36

The method according to Example 35, wherein correcting for the portionof the rendered span of the reference television advertisement that doesnot match the reference television advertisement further comprisessubtracting the portion of the rendered span of the reference televisionadvertisement from the reference television advertisement.

Example 37

The method according to Example 34, wherein correcting for the portionof the rendered span of the reference television advertisement that doesnot match the reference television advertisement comprises determiningthat the portion of the rendered span of the television advertisement isfollowed in the stream of fingerprints by a television content, whereinthe television content is one of chronologically continuous ordiscontinuous relative to an original broadcast.

Example 38

The method according to Example 37, further comprising determining thatthe television content is chronologically continuous and determiningthat the television content was broadcast by a same broadcast network,relative to a broadcast network which broadcast the stream offingerprints comprising the rendered span of the reference televisionadvertisement.

Example 39

The method according to Example 37, further comprising determining thatthe television content is chronologically continuous and determiningthat the television content was broadcast by a different broadcastnetwork, relative to a broadcast network which broadcast the stream offingerprints comprising the rendered span of the reference televisionadvertisement, indicating a change of channel.

Example 40

The method according to Example 37, further comprising determining thatthe television content is chronologically discontinuous relative to thestream of fingerprints comprising the rendered span of the referencetelevision advertisement, indicating a fast forward.

Example 41

The method according to Example 29, further comprising characterizingthe television advertisement as at least one of live, time shifted, oron-demand.

Example 42

The method according to Example 29, further comprising determining anaverage of the view rate of the television advertisement by more thanone television.

Example 43

The method according to Example 42, further comprising averaging theaverage of the view rate of the television advertisement by more thanone television across at least one of a broadcast network, a locale, ora daypart.

Example 44

The method according to Example 42, further comprising determining anaverage completion rate of the television advertisement, wherein theaverage completion rate of the television advertisement comprises apercentage of renderings in which the rendered television advertisementwas rendered without interruption.

Example 45

The method according to Example 42, further comprising outputting theaverage view rate relative to, in conjunction with, or as part of abenchmark.

Example 46

The method according to Example 45, wherein the benchmark comprises atleast one of: an average view rate for all television advertisements; anaverage view rate for all television advertisements of an industry; anaverage view rate for all television advertisements of a productadvertised in the television advertisement; a view rate of a broadcastadvertisement associated with a competitor of the product advertised inthe television advertisement; an average view rate of all broadcastadvertisements associated with a competitor of the product advertised inthe television advertisement; a view rate of all televisionadvertisements for all broadcast networks; or any combination of theabove.

Example 47

The method according to Example 42, further comprising determining apeak drop-off point for the television advertisement.

Example 48

The method according to Example 47, wherein a drop-off point comprises atime, relative to the start of the television advertisement, whenrendering of the television advertisement is discontinued before an endof the reference television advertisement and wherein the peak drop-offpoint comprises the peak of a set of drop-off points by the more thanone television.

Example 49

A method of preparing modified reference advertisements, comprising:identifying a reference advertisement broadcast by a broadcast networkin a modified format; creating a modification of the referenceadvertisement according to the modified format; storing the modificationof the reference advertisement in the library of referenceadvertisements in association with the reference advertisement.

Example 50

The method according to Example 49, wherein the modified formatcomprises a least one of a graphical modification and an encodingmodification.

Example 51

The method according to Example 50, wherein the graphical modificationcomprises an insert area.

Example 52

The method according to Example 51, wherein the graphical modificationcomprises a reduced display area of the reference advertisement, whereinthe reduced display area of the reference advertisement accommodates theinsert area.

Example 53

The method according to Example 52, wherein the insert area comprises atleast one of text or graphics and wherein the insert area is locatedabove, below, or beside the reference advertisement.

Example 54

The method according to Example 50, wherein the graphical modificationcomprises an aspect ratio change.

Example 55

The method according to Example 50, wherein the graphical modificationcomprises an overlay or underlay.

Example 56

The method according to Example 49, further comprising identifyingadvertisements by receiving a set of viewing data from a smart TV, theset of viewing data comprising an sample of broadcast content receivedby the smart TV, and determining that the sample of broadcast contentcorresponds to the modification of the reference advertisement.

Example 57

An computer apparatus to determine a view rate of a televisionadvertisement, comprising: means to receive from a remote television astream of fingerprints of television content rendered by the remotetelevision, means to determine a reference television advertisement inthe stream of fingerprints, means to determine a rendered span of thereference television advertisement in the stream of fingerprints, andmeans to determine the view rate of the television advertisementaccording to the rendered span of the reference television advertisementin the stream of fingerprints.

Example 58

The apparatus according to Example 57, wherein means to determine therendered span of the reference television advertisement in the stream offingerprints comprises means to determine a percentage of the referencetelevision advertisement corresponding to the stream of fingerprints.

Example 59

The apparatus according to Example 58, wherein the percentage of thereference television advertisement are bucketized into viewingquartiles.

Example 60

The apparatus according to Example 59 wherein the quartiles comprise afirst quartile for 0 to 25 percent of the reference televisionadvertisement rendered, a second quartile for 26 to 50 percent of thereference television advertisement rendered, a third quartile for 51 to75 percent of the reference television advertisement rendered, and aforth quartile for 76 to 100 percent of the reference televisionadvertisement rendered.

Example 61

The apparatus according to Example 57, wherein to determine the renderedspan of the reference television advertisement in the stream offingerprints comprises to determine where the rendered span of thereference television advertisement in the stream of fingerprints beginsrelative to a start of the reference television advertisement.

Example 62

The apparatus according to Example 57, further comprising means tocorrect for a portion of the rendered span of the reference televisionadvertisement that does not match a portion of the reference televisionadvertisement.

Example 63

The apparatus according to Example 62, wherein means to correct for theportion of the rendered span of the reference television advertisementthat does not match the portion of the reference televisionadvertisement comprises means to determine that the portion of therendered span is an insert inserted into a specific portion of thereference television advertisement.

Example 64

The apparatus according to Example 63, wherein means to correct for theportion of the rendered span of the reference television advertisementthat does not match the reference television advertisement furthercomprises means to subtract the portion of the rendered span of thereference television advertisement from the reference televisionadvertisement.

Example 65

The apparatus according to Example 62, wherein means to correct for theportion of the rendered span of the reference television advertisementthat does not match the reference television advertisement comprises tomeans to determine that the portion of the rendered span of thetelevision advertisement is followed in the stream of fingerprints by atelevision content, wherein the television content is one ofchronologically continuous or discontinuous relative to an originalbroadcast.

Example 66

The apparatus according to Example 65, further comprising means todetermine that the television content is chronologically continuous andmeans to determine that the television content was broadcast by a samebroadcast network, relative to a broadcast network which broadcast thestream of fingerprints comprising the rendered span of the referencetelevision advertisement.

Example 67

The apparatus according to Example 65, further comprising means todetermine that the television content is chronologically continuous andmeans to determine that the television content was broadcast by adifferent broadcast network, relative to a broadcast network whichbroadcast the stream of fingerprints comprising the rendered span of thereference television advertisement, indicating a change of channel.

Example 68

The apparatus according to Example 65, further comprising means todetermine that the television content is chronologically discontinuousrelative to the stream of fingerprints comprising the rendered span ofthe reference television advertisement, indicating a fast forward.

Example 69

The apparatus according to Example 57, further comprising means tocharacterize the television advertisement as at least one of live, timeshifted, or on-demand.

Example 70

The apparatus according to Example 57, further comprising means todetermine an average of the view rate of the television advertisement bymore than one television.

Example 71

The apparatus according to Example 70, further comprising means toaverage the average of the view rate of the television advertisement bymore than one television across at least one of a broadcast network, alocale, or a daypart.

Example 72

The apparatus according to Example 70, further comprising means todetermine an average completion rate of the television advertisement,wherein the average completion rate of the television advertisementcomprises a percentage of renderings in which the rendered televisionadvertisement was rendered without interruption.

Example 73

The apparatus according to Example 70, further comprising means tooutput the average view rate relative to, in conjunction with, or aspart of a benchmark.

Example 74

The apparatus according to Example 73, wherein the benchmark comprisesat least one of: an average view rate for all television advertisements;an average view rate for all television advertisements of an industry;an average view rate for all television advertisements of a productadvertised in the television advertisement; a view rate of a broadcastadvertisement associated with a competitor of the product advertised inthe television advertisement; an average view rate of all broadcastadvertisements associated with a competitor of the product advertised inthe television advertisement; a view rate of all televisionadvertisements for all broadcast networks; or any combination of theabove.

Example 75

The apparatus according to Example 70, further comprising means todetermine a peak drop-off point for the television advertisement.

Example 76

The apparatus according to Example 75, wherein a drop-off pointcomprises a time, relative to the start of the television advertisement,when rendering of the television advertisement is discontinued before anend of the reference television advertisement and wherein the peakdrop-off point comprises the peak of a set of drop-off points by themore than one television.

Example 77

An apparatus to prepare modified reference advertisements, comprising:means to identify a reference advertisement broadcast by a broadcastnetwork in a modified format; means to create a modification of thereference advertisement according to the modified format; means to storethe modification of the reference advertisement in the library ofreference advertisements in association with the referenceadvertisement.

Example 78

The apparatus according to Example 77, wherein the modified formatcomprises a least one of a graphical modification and an encodingmodification.

Example 79

The apparatus according to Example 78, wherein the graphicalmodification comprises an insert area.

Example 80

The apparatus according to Example 79, wherein the graphicalmodification comprises a reduced display area of the referenceadvertisement, wherein the reduced display area of the referenceadvertisement accommodates the insert area.

Example 81

The apparatus according to Example 80, wherein the insert area comprisesat least one of text or graphics and wherein the insert area is locatedabove, below, or beside the reference advertisement.

Example 82

The apparatus according to Example 78, wherein the graphicalmodification comprises an aspect ratio change.

Example 83

The apparatus according to Example 78, wherein the graphicalmodification comprises an overlay or underlay.

Example 84

The apparatus according to Example 77, further comprising means toidentify advertisements by means to receive a set of viewing data from asmart TV, the set of viewing data comprising an sample of broadcastcontent received by the smart TV, and means to determine that the sampleof broadcast content corresponds to the modification of the referenceadvertisement.

Example 85

One or more computer-readable media comprising instructions that cause acomputer device, in response to execution of the instructions by one ormore processors of the sensory output computer device, to: receive froma remote television a stream of fingerprints of television contentrendered by the remote television, determine a reference televisionadvertisement in the stream of fingerprints, determine a rendered spanof the reference television advertisement in the stream of fingerprints,and determine the view rate of the television advertisement according tothe rendered span of the reference television advertisement in thestream of fingerprints.

Example 86

The computer-readable media according to Example 85, wherein determinethe rendered span of the reference television advertisement in thestream of fingerprints comprises determine a percentage of the referencetelevision advertisement corresponding to the stream of fingerprints.

Example 87

The computer-readable media according to Example 86, wherein thepercentage of the reference television advertisement are bucketized intoviewing quartiles.

Example 88

The computer-readable media according to Example 87 wherein thequartiles comprise a first quartile for 0 to 25 percent of the referencetelevision advertisement rendered, a second quartile for 26 to 50percent of the reference television advertisement rendered, a thirdquartile for 51 to 75 percent of the reference television advertisementrendered, and a forth quartile for 76 to 100 percent of the referencetelevision advertisement rendered.

Example 89

The computer-readable media according to Example 85, wherein determinethe rendered span of the reference television advertisement in thestream of fingerprints comprises determine where the rendered span ofthe reference television advertisement in the stream of fingerprintsbegins relative to a start of the reference television advertisement.

Example 90

The computer-readable media according to Example 85, further comprisingcorrect for a portion of the rendered span of the reference televisionadvertisement that does not match a portion of the reference televisionadvertisement.

Example 91

The computer-readable media according to Example 90, wherein correct forthe portion of the rendered span of the reference televisionadvertisement that does not match the portion of the referencetelevision advertisement comprises determine that the portion of therendered span is an insert inserted into a specific portion of thereference television advertisement.

Example 92

The computer-readable media according to Example 91, wherein correct forthe portion of the rendered span of the reference televisionadvertisement that does not match the reference television advertisementfurther comprises subtract the portion of the rendered span of thereference television advertisement from the reference televisionadvertisement.

Example 93

The computer-readable media according to Example 90, wherein correct forthe portion of the rendered span of the reference televisionadvertisement that does not match the reference television advertisementcomprises determine that the portion of the rendered span of thetelevision advertisement is followed in the stream of fingerprints by atelevision content, wherein the television content is one ofchronologically continuous or discontinuous relative to an originalbroadcast.

Example 94

The computer-readable media according to Example 93, further comprisingdetermine that the television content is chronologically continuous anddetermine that the television content was broadcast by a same broadcastnetwork, relative to a broadcast network which broadcast the stream offingerprints comprising the rendered span of the reference televisionadvertisement.

Example 95

The computer-readable media according to Example 93, further comprisingdetermine that the television content is chronologically continuous anddetermine that the television content was broadcast by a differentbroadcast network, relative to a broadcast network which broadcast thestream of fingerprints comprising the rendered span of the referencetelevision advertisement, indicating a change of channel.

Example 96

The computer-readable media according to Example 93, further comprisingdetermine that the television content is chronologically discontinuousrelative to the stream of fingerprints comprising the rendered span ofthe reference television advertisement, indicating a fast forward.

Example 97

The computer-readable media according to Example 85, further comprisingcharacterize the television advertisement as at least one of live, timeshifted, or on-demand.

Example 98

The computer-readable media according to Example 85, further comprisingdetermine an average of the view rate of the television advertisement bymore than one television.

Example 99

The computer-readable media according to Example 98, further comprisingaverage the average of the view rate of the television advertisement bymore than one television across at least one of a broadcast network, alocale, or a daypart.

Example 100

The computer-readable media according to Example 98, further comprisingdetermine an average completion rate of the television advertisement,wherein the average completion rate of the television advertisementcomprises a percentage of renderings in which the rendered televisionadvertisement was rendered without interruption.

Example 101

The computer-readable media according to Example 98, further comprisingoutput the average view rate relative to, in conjunction with, or aspart of a benchmark.

Example 102

The computer-readable media according to Example 101, wherein thebenchmark comprises at least one of: an average view rate for alltelevision advertisements; an average view rate for all televisionadvertisements of an industry; an average view rate for all televisionadvertisements of a product advertised in the television advertisement;a view rate of a broadcast advertisement associated with a competitor ofthe product advertised in the television advertisement; an average viewrate of all broadcast advertisements associated with a competitor of theproduct advertised in the television advertisement; a view rate of alltelevision advertisements for all broadcast networks; or any combinationof the above.

Example 103

The computer-readable media according to Example 98, further comprisingdetermine a peak drop-off point for the television advertisement.

Example 104

The computer-readable media according to Example 103, wherein a drop-offpoint comprises a time, relative to the start of the televisionadvertisement, when rendering of the television advertisement isdiscontinued before an end of the reference television advertisement andwherein the peak drop-off point comprises the peak of a set of drop-offpoints by the more than one television.

Example 105

One or more computer-readable media comprising instructions that cause acomputer device, in response to execution of the instructions by one ormore processors of the sensory output computer device, to: identify areference advertisement broadcast by a broadcast network in a modifiedformat; create a modification of the reference advertisement accordingto the modified format; store the modification of the referenceadvertisement in the library of reference advertisements in associationwith the reference advertisement.

Example 106

The computer-readable media according to Example 105, wherein themodified format comprises a least one of a graphical modification and anencoding modification.

Example 107

The computer-readable media according to Example 106, wherein thegraphical modification comprises an insert area.

Example 108

The computer-readable media according to Example 107, wherein thegraphical modification comprises a reduced display area of the referenceadvertisement, wherein the reduced display area of the referenceadvertisement accommodates the insert area.

Example 109

The computer-readable media according to Example 108, wherein the insertarea comprises at least one of text or graphics and wherein the insertarea is located above, below, or beside the reference advertisement.

Example 110

The computer-readable media according to Example 106, wherein thegraphical modification comprises an aspect ratio change.

Example 111

The computer-readable media according to Example 106, wherein thegraphical modification comprises an overlay or underlay.

Example 112

The computer-readable media according to Example 105, further comprisingidentify advertisements by receive a set of viewing data from a smartTV, the set of viewing data comprising an sample of broadcast contentreceived by the smart TV, and determine that the sample of broadcastcontent corresponds to the modification of the reference advertisement.

1. An apparatus for preparing modified reference advertisements,comprising: a computer processor and a memory; a datastore comprisingreference advertisements; an ad modification module coupled to thecomputer processor, the ad modification module to modify referenceadvertisements, wherein ad modification module is to: identify areference advertisement broadcast by a broadcast network in a modifiedformat; create a modification of the reference advertisement accordingto the modified format; store the modification of the referenceadvertisement in the datastore of reference advertisements inassociation with reference advertisement.
 2. The apparatus according toclaim 1, wherein the modified format comprises a least one of agraphical modification and an encoding modification.
 3. The apparatusaccording to claim 2, wherein the graphical modification comprises aninsert area.
 4. The apparatus according to claim 3, wherein thegraphical modification comprises a reduced display area of the referenceadvertisement, wherein the reduced display area of the referenceadvertisement accommodates the insert area.
 5. The apparatus accordingto claim 4, wherein the insert area comprises at least one of text orgraphics and wherein the insert area is located above, below, or besidethe reference advertisement.
 6. The apparatus according to claim 2,wherein the graphical modification comprises an aspect ratio change. 7.The apparatus according to claim 2, wherein the graphical modificationcomprises an overlay or underlay.
 8. The apparatus according to claim 1,further comprising an ad harvesting module coupled to the computerprocessor, the ad harvesting module to identify advertisements, whereinidentify advertisements, the ad harvesting module is to receive a set ofviewing data from a smart TV, the set of viewing data comprising ansample of broadcast content received by the smart TV, and determine thatthe sample of broadcast content corresponds to the modification of thereference advertisement.
 9. A method of preparing modified referenceadvertisements, comprising: identifying a reference advertisementbroadcast by a broadcast network in a modified format; creating amodification of the reference advertisement according to the modifiedformat; storing the modification of the reference advertisement in thelibrary of reference advertisements in association with the referenceadvertisement.
 10. The method according to claim 9, wherein the modifiedformat comprises a least one of a graphical modification and an encodingmodification.
 11. The method according to claim 10, wherein thegraphical modification comprises an insert area.
 12. The methodaccording to claim 11, wherein the graphical modification comprises areduced display area of the reference advertisement, wherein the reduceddisplay area of the reference advertisement accommodates the insertarea.
 13. The method according to claim 12, wherein the insert areacomprises at least one of text or graphics and wherein the insert areais located above, below, or beside the reference advertisement.
 14. Themethod according to claim 10, wherein the graphical modificationcomprises an aspect ratio change.
 15. The method according to claim 10,wherein the graphical modification comprises an overlay or underlay. 16.The method according to claim 9, further comprising identifyingadvertisements by receiving a set of viewing data from a smart TV, theset of viewing data comprising an sample of broadcast content receivedby the smart TV, and determining that the sample of broadcast contentcorresponds to the modification of the reference advertisement.
 17. Oneor more computer-readable media comprising instructions that cause acomputer device, in response to execution of the instructions by one ormore processors of the sensory output computer device, to: identify areference advertisement broadcast by a broadcast network in a modifiedformat; create a modification of the reference advertisement accordingto the modified format; store the modification of the referenceadvertisement in the library of reference advertisements in associationwith the reference advertisement.
 18. The computer-readable mediaaccording to claim 17, wherein the modified format comprises a least oneof a graphical modification and an encoding modification.
 19. Thecomputer-readable media according to claim 18, wherein the graphicalmodification comprises an insert area.
 20. The computer-readable mediaaccording to claim 19, wherein the graphical modification comprises areduced display area of the reference advertisement, wherein the reduceddisplay area of the reference advertisement accommodates the insertarea.
 21. The computer-readable media according to claim 20, wherein theinsert area comprises at least one of text or graphics and wherein theinsert area is located above, below, or beside the referenceadvertisement.
 22. The computer-readable media according to claim 18,wherein the graphical modification comprises an aspect ratio change. 23.The computer-readable media according to claim 18, wherein the graphicalmodification comprises an overlay or underlay.
 24. The computer-readablemedia according to claim 17, further comprising identify advertisementsby receive a set of viewing data from a smart TV, the set of viewingdata comprising an sample of broadcast content received by the smart TV,and determine that the sample of broadcast content corresponds to themodification of the reference advertisement.